1. Add member variable 'DDim dims_' and a getter function 'dims()'.
'dims' is supposed to hold tensor's shape during Op::InferShape.
2. Remove 'mutable_data' which use default Place. User must specify a
explicit Place when call 'mutable_data'.
3. A PlaceHolder may be shared by more than one tensor, and some of them may be the others' slices. So we add a new member variable 'offset_' for Tensor, which is used to show the byte offset between PlaceHolder::ptr_ and where tensor's data really begins.
4. Add functions 'ShareDataFrom' and 'Slice' for Tensor.

TODO: Tensor needs a 'CopyFrom' function.

* init op_registry.h

* dev op_registry.h

* add 'attr_checker.h', which is a draft of op attribute checker.

* rename some macro parameters

* 1. Use `Attribute` and `AttributeMap` instead of `OpDesc`. `AttributeMap` is a unordered_map of <string, Attribute>, and `Attribute` is a boost::variant object to hold multiple types of attribute value.
2. Use `PADDLE_ENFORCE` to print checkers' fail message.
3. Abstract default value operations to a new function: `DefaultChecker`.

* rename DefaultChecker to DefaultValueSetter

ZZ

* Finish op_registry

1. Complete the development of interfaces between OpRegistry and
Protobuf.
2. Add unit test for op_registry.h

* Add demo and test of custome checker

* fix merge conflict

Python should be able to manipulate Protobuf message because:

1. Python's `create_op_creation_methods` take the `OpProto` array to
   generate all `op_creation_methods` in RunTime.

2. All `op_creation_methods` will create an `OpDesc` and pass it to
   Paddle C++ method `CreateOp` and return the Op handle.

Here is the list of what is added in this commit:

* Add `protobuf_generate_python` if it is not defined.
  * Before cmake 3.4, `protobuf_generate_python` is not defined. Just
    copy the implementation of that function in `protobuf.cmake`
* Add `py_proto_compile` function in `cmake/generic.cmake`.
  * It follows bazel's API interface.
    * https://github.com/pubref/rules_protobuf#rules
* Add an empty package named `paddle.v2.framework`, all python code of
  `paddle::framework` will be in that package.
* Generate protobuf's python module `__init__.py` by `touch` while
  compiling.
* Change setup.py.in, make `paddle.v2.framework.proto` uses the
  generated protobuf pythons.

* add op_desc.proto

In Operator design, we need a proto message to describe an Operator.
Third-party language such as python can build this proto message and use
AddOp(const OpDesc& op_desc) of Paddle core to construct an Op in the
Network.

It will fix #2728.

Maybe it is silly to `target_link_libraries` for static library,
because a static library do not need to link other libraries. But
it will tell cmake how to propagate dependencies.

The solution comes from
[here](http://floooh.github.io/2016/01/12/cmake-dependency-juggling.html).

* Also change op_proto_test DEPS for testing this fix works.

Missing DEPS will cause compile error when parallel is large.

* move net_design to framework

* change CreateNet result to unique_ptr

* rename "ScratchNet" -> "PlainNet"

* add three methods to NetBase

* add NetBuilder

* add InferShape to NetBuilder.Run

* rename ApplyGradient, ApplyOptimizer -> AddGradientOps, AddOptimiz

* rename PlainNet::CreateNet -> BuildNet

* add Error and other rename actions

OpProto is a proto message that helps 3rd-party language bindings, e.g.
`Python`, to generate operator creation methods. The operator creation
method is the low-level API for 3rd-party language bindings. Op creation
methods take the user's input in that language, and convert users inputs
into `OpDesc` message, then passing that `OpDesc` message to Paddle's
C++ core and create an operator.

* A separated `attr_type.proto` is added, because that file wound
  be included by `op_desc.proto` in future.